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Article

Smyly Bannerman

Discusses the methods of sensitivity analysis in use generally andby the property appraisal profession. Proposes a simplified structuredand systematic technique of…

Abstract

Discusses the methods of sensitivity analysis in use generally and by the property appraisal profession. Proposes a simplified structured and systematic technique of selecting critical or sensitive factors for sensitivity analysis in property development and investment appraisal. Concludes that sensitivity analysis has become an integral part of property appraisal.

Details

Journal of Property Valuation and Investment, vol. 11 no. 3
Type: Research Article
ISSN: 0960-2712

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Article

Xin Li, Jianzhong Shang and Hong Zhu

This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes…

Abstract

Purpose

This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins and inertial navigation system (INSs), and establish the assembly process state space model for their assembly sensitivity research.

Design/methodology/approach

To date, the process-related errors that cause large variations in key product characteristics remains one of the most critical research topics in assembly sensitivity analysis. This paper focuses on the unique challenges brought about by the multi-station system: a system-level model for characterizing the variation propagation in the entire process, and the necessity of describing the system response to variation inputs at both station-level and single fixture-level scales. State space representation is used to describe the propagation of variation in such a multi-station process, incorporating assembly process parameters such as fixture-locating layout at individual stations and station-to-station locating layout change.

Findings

Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given assembly process parameters.

Originality/value

A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.

Details

Assembly Automation, vol. 37 no. 2
Type: Research Article
ISSN: 0144-5154

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Article

Yidu Zhang, Yongshou Liu and Qing Guo

This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty.

Abstract

Purpose

This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty.

Design/methodology/approach

The uncertainty information of the input variable is considered as convex-probability hybrid uncertainty. Moment-independent variable global sensitivity index based on the system failure probability is proposed to quantify the effect of the input variable on the system failure probability. Two-mode sensitivity indices are adopted to characterize the effect of each failure mode on the system failure probability. The method based on active learning Kriging (ALK) model with a truncated candidate regions (TCR) is adopted to evaluate the systems failure probability, as well as sensitivity index and this method is termed as ALK-TCR.

Findings

The results of five examples demonstrate the effectiveness of the sensitivity index and the efficiency of the ALK-TCR method in solving the problem of multiple failure modes based on the convex-probability hybrid uncertainty.

Originality/value

Convex-probability hybrid uncertainty is considered on system reliability analysis. Moment-independent variable sensitivity index based on the system failure probability is proposed. Mode sensitivity indices are extended to hybrid uncertain reliability model. An effective global sensitivity analysis approach is developed for the multiple failure modes based on convex-probability hybrid uncertainty.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

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Article

B.J. Henz, K.K. Tamma, R. Kanapady, N.D. Ngo and P.W. Chung

The resin transfer molding process for composites manufacturing consists of either of two considerations, namely, the fluid flow analysis through a porous fiber preform…

Abstract

The resin transfer molding process for composites manufacturing consists of either of two considerations, namely, the fluid flow analysis through a porous fiber preform where the location of the flow front is of fundamental importance, and the combined flow/heat transfer/cure analysis. In this paper, the continuous sensitivity formulations are developed for the process modeling of composites manufactured by RTM to predict, analyze, and optimize the manufacturing process. Attention is focused here on developments for isothermal flow simulations, and various illustrative examples are presented for sensitivity analysis of practical applications which help serve as a design tool in the process modeling stages.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 13 no. 4
Type: Research Article
ISSN: 0961-5539

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Article

Wakae Kozukue and Ichiro Hagiwara

One of the authors has already formulated the sensitivity analysis for a coupled structural‐acoustic system and applied the method in order to obtain modal sensitivities

Abstract

One of the authors has already formulated the sensitivity analysis for a coupled structural‐acoustic system and applied the method in order to obtain modal sensitivities and modal frequency response sensitivities for the sound pressure level at peak frequency points. However, for the development of a vehicle, not only the reduction of peak frequency level but also that of integral of noise for a specified frequency range is desired. For investigating this it is considered effective to use sensitivities of integrated sound pressure level for a specified frequency range. Thus a “sound pressure level integral” has been developed, which is the integrated value of sound pressure level, and further “sensitivity of sound pressure level integral”. Shows how an integral analysis process is performed, and how vibration and noise can be reduced.

Details

Engineering Computations, vol. 13 no. 5
Type: Research Article
ISSN: 0264-4401

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Article

Xuchun Ren and Sharif Rahman

This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based…

Abstract

Purpose

This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based design optimization (RBDO) subject to mixed design variables comprising both distributional and structural design variables.

Design/methodology/approach

The method involves a new augmented PDD of a high-dimensional stochastic response for statistical moments and reliability analyses; an integration of the augmented PDD, score functions, and finite-difference approximation for calculating the sensitivities of the first two moments and the failure probability with respect to distributional and structural design variables; and standard gradient-based optimization algorithms.

Findings

New closed-form formulae are presented for the design sensitivities of moments that are simultaneously determined along with the moments. A finite-difference approximation integrated with the embedded Monte Carlo simulation of the augmented PDD is put forward for design sensitivities of the failure probability.

Originality/value

In conjunction with the multi-point, single-step design process, the new method provides an efficient means to solve a general stochastic design problem entailing mixed design variables with a large design space. Numerical results, including a three-hole bracket design, indicate that the proposed methods provide accurate and computationally efficient sensitivity estimates and optimal solutions for RDO and RBDO problems.

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Article

R. Chowdhury and S. Adhikari

High‐dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high‐dimensional relationships between…

Abstract

Purpose

High‐dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high‐dimensional relationships between sets of input and output model variables. It is an efficient formulation of the system response, if higher‐order cooperative effects are weak, allowing the physical model to be captured by the lower‐order terms. The paper's aim is to develop a new computational tool for estimating probabilistic sensitivity of structural/mechanical systems subject to random loads, material properties and geometry.

Design/methodology/approach

When first‐order HDMR approximation of the original high‐dimensional limit state is not adequate to provide the desired accuracy to the sensitivity analysis, this paper presents an enhanced HDMR (eHDMR) method to represent the higher‐order terms of HDMR expansion by expressions similar to the lower‐order ones with monomial multipliers. The accuracy of the HDMR expansion can be significantly improved using preconditioning with a minimal number of additional input‐output samples without directly invoking the determination of second‐ and higher‐order terms. As a part of this effort, the efficacy of HDMR, which is recently applied to uncertainty analysis, is also demonstrated. The method is based on computing eHDMR approximation of system responses and score functions associated with probability distribution of a random input. Surrogate model is constructed using moving least squares interpolation formula. Once the surrogate model form is defined, both the probabilistic response and its sensitivities can be estimated from a single probabilistic analysis, without requiring the gradients of performance functions.

Findings

The results of two numerical examples involving mathematical function and structural/solid‐mechanics problems indicate that the sensitivities obtained using eHDMR approximation provide significant accuracy when compared with the conventional Monte Carlo method, while requiring fewer original model simulations.

Originality/value

This is the first time where application of eHDMR concepts is explored in the stochastic sensitivity analysis. The present computational approach is valuable to the practical modelling and design community.

Details

Engineering Computations, vol. 27 no. 7
Type: Research Article
ISSN: 0264-4401

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Article

Stefan Schwarz and Ekkehard Ramm

The present contribution deals with the sensitivity analysis and optimization of structures for path‐dependent structural response. Geometrically as well as materially…

Abstract

The present contribution deals with the sensitivity analysis and optimization of structures for path‐dependent structural response. Geometrically as well as materially non‐linear behavior with hardening and softening is taken into account. Prandtl‐Reuss‐plasticity is adopted so that not only the state variables but also their sensitivities are path‐dependent. Because of this the variational direct approach is preferred for the sensitivity analysis. For accuracy reasons the sensitivity analysis has to be consistent with the analysis method evaluating the structural response. The proposed sensitivity analysis as well as its application in structural optimization is demonstrated by several examples.

Details

Engineering Computations, vol. 18 no. 3/4
Type: Research Article
ISSN: 0264-4401

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Article

Ming-Lang Tseng, Shiou-Yun Jeng, Chun-Wei Lin and Ming K. Lim

Construction and demolition waste (CDW) continuously causes environmental and social problems. These formidable challenges lead to sustainable issues and are an…

Abstract

Purpose

Construction and demolition waste (CDW) continuously causes environmental and social problems. These formidable challenges lead to sustainable issues and are an increasingly urgent issue worldwide. Prior studies have neglected to link the triple bottom line (TBL) to a reliable estimation or empirical model for estimating CDW production performance and lack empirical sensitivity analysis in profit maximization. This study proposes an attribute analysis to build a cost–benefit analysis (CBA) to obtain profit maximization.

Design/methodology/approach

This study uses fuzzy set theory to develop a cost and benefit analysis (CBA) model to assess the sensitivity analysis in terms of its performance on addressing the environmental, economic and social aspects. The model is used to weigh the sum of benefits such as financial gain and total costs of actions taken to mitigate the negative impacts.

Findings

Based on the sensitivity analysis conducted, the environmental, economic and social mean scales were significantly changed, i.e. increased, and profits increased drastically. The results provide an insight into environmental legislation compliance, environmental investment and environmental impact as the cause attributes for the CDW recycling profit increase. The results prove that sensitivity analysis is viable to infer that a sustainable production performance can achieve more revenue and profit through an adequate selection of attributes regarding the TBL aspects to address the firm's uncertainty problem in multiple criteria analysis.

Originality/value

This study builds a CBA model to maximize profits for recycled CDW material by linking of environmental, economic and societal aspects for recycled CDW assessments. It considers a sustainability structure with criteria based on TBL aspects to assess production performance to realize the Sustainable Development Goals and presents fuzzy set theory and sensitivity analysis to solve the uncertainty problem in the construction industry.

Details

Management of Environmental Quality: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1477-7835

Keywords

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Article

Marzieh Jafari and Khaled Akbari

This paper aims to measure the sensitivity of the structure’s deformation numerical model (NM) related to the various types of the design parameters, which is a suitable…

Abstract

Purpose

This paper aims to measure the sensitivity of the structure’s deformation numerical model (NM) related to the various types of the design parameters, which is a suitable method for parameter selection to increase the time of model-updating.

Design/methodology/approach

In this research, a variance-based sensitivity analysis (VBSA) approach is proposed to measure the sensitivity of NM of structures. In this way, the contribution of measurements of the structure (such as design parameter values and geometry) on the output of NM is studied using first-order and total-order sensitivity indices developed by Sobol’. In this way the generated data set of parameters by considering different distributions such as Gaussian or uniform distribution and different order as input along with, the resulted deformation variables of NM as output has been submitted to the Sobol’ indices estimation procedure. To the verification of VBSA results, a gradient-based sensitivity analysis (SA), which is developed as a global SA method has been developed to measure the global sensitivity of NM then implemented over the NM’s results of a tunnel.

Findings

Regarding the estimated indices, it has been concluded that the derived deformation functions from the tunnel’s NM usually are non-additive. Also, some parameters have been determined as most effective on the deformation functions, which can be selected for model-updating to avoid a time-consuming process, so those may better to be considered in the group of updating parameters. In this procedure for SA of the model, also some interactions between the selected parameters with other parameters, which are beneficial to be considered in the model-updating procedure, have been detected. In this study, some parameters approximately (27 per cent of the total) with no effect over the all objective functions have been determined to be excluded from the parameter candidates for model-updating. Also, the resulted indices of implemented VBSA were approved during validation by the gradient-based indices.

Practical implications

The introduced method has been implemented for a circular lined tunnel’s NM, which has been created by Fast Lagrangian Analysis of Continua software.

Originality/value

This paper plans to apply a statistical method, which is global on the results of the NM of a soil structure by a complex system for parameter selection to avoid the time-consuming model-updating process.

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